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jawn's Introduction

Jawn

"Jawn is for parsing jay-sawn."

Origin

The term "jawn" comes from the Philadelphia area. It conveys about as much information as "thing" does. I chose the name because I had moved to Montreal so I was remembering Philly fondly. Also, there isn't a better way to describe objects encoded in JSON than "things". Finally, we get a catchy slogan.

Jawn was designed to parse JSON into an AST as quickly as possible.

Overview

Jawn consists of three parts:

  1. A fast, generic JSON parser
  2. A small, somewhat anemic AST
  3. Support packages which parse to third-party ASTs

Currently Jawn is competitive with the fastest Java JSON libraries (GSON and Jackson) and in the author's benchmarks it often wins. It seems to be faster than any other Scala parser that exists (as of July 2014).

Given the plethora of really nice JSON libraries for Scala, the expectation is that you are here for (1) and (3) not (2).

Quick Start

Jawn supports Scala 2.10 and 2.11. Here's a build.sbt snippet that shows you how to depend on Jawn for your project:

// use this if you just want jawn's parser, and will implement your own facade
libraryDependencies += "org.spire-math" %% "jawn-parser" % "0.6.0"

// use this if you want to use jawn's parser and ast
libraryDependencies += "org.spire-math" %% "jawn-ast" % "0.6.0"

If you want to use Jawn's parser with another project's AST, see the "Supporting external ASTs with Jawn" section. For example, with Spray you would say:

libraryDependencies += "org.spire-math" %% "spray-support" % "0.6.0"

There are a few reasons you might want to do this:

  • The library's built-in parser is significantly slower than Jawn
  • Jawn supports more input types (ByteBuffer, File, etc.)
  • You need asynchronous JSON parsing

Parsing

Jawn's parser is both fast and relatively featureful. Assuming you want to get back an AST of type J and you have a Facade[J] defined, you can use the following parse signatures:

Parser.parseUnsafe[J](String)  J
Parser.parseFromString[J](String)  Try[J]
Parser.parsefromPath[J](String)  Try[J]
Parser.parseFromFile[J](File)  Try[J]
Parser.parseFromChannel[J](ReadableByteChannel)  Try[J]
Parser.parseFromByteBuffer[J](ByteBuffer)  Try[J]

Jawn also supports asynchronous parsing, which allows users to feed the parser with data as it is available. There are three modes:

  • SingleValue waits to return a single J value once parsing is done.
  • UnwrapArray if the top-level element is an array, return values as they become available.
  • ValueStream parser one-or-more json values separated by whitespace

Here's an example:

import jawn.ast
import jawn.AsyncParser

val p = ast.JParser.async(mode = AsyncParser.UnwrapArray)

def chunks: Stream[String] = ...
def sink(j: ast.JValue): Unit = ...

def loop(st: Stream[String]): Either[ParseException, Unit] =
  st match {
    case Stream.End => p.finish().fold(e => e, js => js.foreach(sink))
    case s #:: tail => p.absorb(s).fold(e => e, { js => js.foreach(sink); loop(tail) })
  }
  
loop(chunks)

You can also call jawn.Parser.async[J] to use async parsing with an arbitrary data type.

Supporting external ASTs with Jawn

Jawn currently supports six external ASTs directly:

  • Argonaut (6.0.4)
  • Json4s (3.2.10)
  • Play (2.3.0)
  • Rojoma (2.4.3)
  • Rojoma-v3 (3.0.0)
  • Spray (1.2.6)

Each of these subprojects provides a Parser object (an instance of SupportParser[J]) that is parameterized on the given project's AST (J). The following methods are available:

Parser.parseUnsafe(String)  J
Parser.parseFromString(String)  Try[J]
Parser.parsefromPath(String)  Try[J]
Parser.parseFromFile(File)  Try[J]
Parser.parseFromChannel(ReadableByteChannel)  Try[J]
Parser.parseFromByteBuffer(ByteBuffer)  Try[J]

These methods parallel those provided by jawn.Parser.

For the following snippets, XYZ is one of (argonaut, json4s, play, rojoma, rojoma-v3 or spray):

This is how you would include the subproject in build.sbt:

libraryDependencies += "org.spire-math" %% "XYZ-support" % "0.6.0"

This is an example of how you might use the parser into your code:

import jawn.support.XYZ.Parser

val myResult = Parser.parseFromString(myString)

Do-It-Yourself Parsing

Jawn supports building any JSON AST you need via type classes. You benefit from Jawn's fast parser while still using your favorite Scala JSON library. This mechanism is also what allows Jawn to provide "support" for other libraries' ASTs.

To include Jawn's parser in your project, add the following snippet to your build.sbt file:

libraryDependencies += "org.spire-math" %% "jawn-parser" % "0.6.0"

To support your AST of choice, you'll want to define a jawn.Facade[J] instance, where the J type parameter represents the base of your JSON AST. For example, here's a facade that supports Spray:

import spray.json._
object Spray extends SimpleFacade[JsValue] {
  def jnull() = JsNull
  def jfalse() = JsFalse
  def jtrue() = JsTrue
  def jnum(s: String) = JsNumber(s)
  def jint(s: String) = JsNumber(s)
  def jstring(s: String) = JsString(s)
  def jarray(vs: List[JsValue]) = JsArray(vs)
  def jobject(vs: Map[String, JsValue]) = JsObject(vs)
}

Most ASTs will be easy to define using the SimpleFacade or MutableFacade traits. However, if an ASTs object or array instances do more than just wrap a Scala collection, it may be necessary to extend Facade directly.

You can also look at the facades used by the support projects to help you create your own. This could also be useful if you wanted to use an older version of a supported library.

Dependencies

jawn-parser has no dependencies other than Scala itself.

jawn-ast depends on Spire in order to provide type class instances.

The various support projects (e.g. argonaut-support) depend on the library they are supporting.

Profiling

Jawn provides benchmarks to help compare various JSON parsers on a wide range of input files. You can run the benchmarks from SBT with:

> benchmark/run

Any JSON files you put in benchmark/src/main/resources will be included in the ad-hoc benchmark. There is a Python script I've used to generate random JSON data called randjson.py which is a bit quirky but does seem to work. I test on this random JSON as well as data from projects I've worked on.

(I also test with larger data sets (100-600M) but for obvious reasons I don't distribute this JSON in the project.)

Of course, your mileage may vary, and these results do vary somewhat based on file size, file structure, etc.

I have tried to understand the libraries well enough to write the most optimal code for loading a file (given a path) and parsing it to a simple JSON AST. Pull requests to update versions and improve usage are welcome.

Disclaimers

Jawn only supports UTF-8 when parsing bytes. This might change in the future, but for now that's the target case. You can always decode your data to a string, and handle the character set decoding using Java's standard tools.

Jawn's AST is intended to be a proof of concept of a very lightweight AST. It lacks most of the fancy operators and DSLs of other libraries.

Copyright and License

All code is available to you under the MIT license, available at http://opensource.org/licenses/mit-license.php.

Copyright Erik Osheim, 2012-2014.

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